Costing for Availability - University of Bath · 2019-10-31 · Costing for Availability 1 Dr Linda...

Costing for Availability


Purpose of this booklet

ContentsThe Project Team

The Challenges of Costing Availability

The Systems-based Approach

Identification & Representation of the System of Interest

Quantification

Way forward

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page numbers

This booklet has been written for you to refer to after the workshop. The booklet consists of six core sections ranging from the definition of main concepts to a top-level conceptual outline of our proposed systems-based approach to costing availability. It provides an overview of what we have covered in the workshop.

Dr Linda Newnes Dr Mey GohHead of Costing Research LecturerDepartment of Mechanical Engineering Wolfson School of Mechanical & Manufacturing EngineeringUniversity of Bath Loughborough UniversityClaverton Down LoughboroughBath LeicsBA2 7AY LE11 3TU

Email: [email protected] Email: [email protected]: +(44) 1225 386291 Phone: +(44)1509 227672

This booklet has been funded through the EPSRC Impact Acceleration Accounts at the University of Bathand Loughborough University

Costing for Availability 1

Dr Linda Newnes, University of BathDr Newnes is Head of Costing Research in the Department of Mechanical Engineering, University of Bath. Her research focuses on through life costing from concept design through to the in-service/in-use phases and re-use/disposal. The sectors/application areas for her activities include for example; aerospace, defence, medical device design, oil and gas, water, green technologies, modelling uncertainty in through life costing, modelling in-service costs and trade-off analysis between specification and cost. She has published over 100-refereed papers, involved with consortium grants worth over £32M and individual projects of £4.5M. She has embedded her research into industry identifying over 63% in cost reduction, provides CPD and undergraduate courses on cost estimating.Contact: [email protected]

Dr Ettore Settanni, University of BathDr Ettore Settanni is a post doctoral researcher at the University of Bath and is the lead researcher in the research project Costing for Avionic Through-Life Availability (CATA) working with DE&S, GE Aviation and Military Air Information, BAE Systems. He provides inter-disciplinary methodological expertise for assessing and modelling the Through Life Costs of product-service-systems. He has received the Emerald Literati Network’s Outstanding Paper Award 2011 for his research published in the Journal of Modelling in Management.Contact: [email protected]

Mr Nils Thenent, University of BathNils started his career in aviation as an aircraft maintenance apprentice and avionics technician. He went on to study aircraft design and aerospace engineering at the Aachen University of Applied Sciences, Germany and recently completed his Ph.D. at the University of Bath, UK in the field of cost estimation for integrated product-service offerings in aviation. Nils has been working with major aerospace companies, such as Lufthansa Technik, Pratt & Whitney Canada, GE Aviation and BAE Systems, and has presented his research at national and international conferences. His interests include aircraft technology, aviation management, continuous improvement, and aviation safety.Contact: [email protected]

Dr Glenn Parry, University of the West of EnglandDr Glenn Parry is Associate Professor of Strategy and Operations Management at Bristol Business School, UWE. Dr Parry’s work is characterised by an approach of partnering with industry to develop creative solutions to business challenges. His expertise is in service, supply chains and strategy and his work is always practically focussed, backed by academic rigour. He has managed and contributed towards research consortia within the automotive, aerospace, music and construction industries. He has published in numerous international journals and is on the editorial board for the Journal of Enterprise Transformation.Contact: [email protected]

Dr Yee Mey Goh, University of LoughboroughDr Goh is a Lecturer in Wolfson School of Mechanical and Manufacturing Engineering, Loughborough University. Her main research interests lie in methods and techniques for identifying and managing uncertainties through life, for design, manufacture and operational support. Her research applications cover energy, aerospace and defence, automotive and railway sectors. She is on the scientific committees for leadinginternational conferences (ASME IDETC/CIE, ICED and DESIGN). She has been an investigator on research programmes worth over £5 M. She has published widely in high quality academic journals and has experience in knowledge transfer activities.Contact: [email protected]

The Project Team

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GE Aviation

BAE Systems, Military Air and Information

The UK Ministry of Defence, CAAS

Industrial Collaborators

Funding bodies



Further readingsNewnes, Linda B.; Settanni, Ettore; Thenent, Nils Elias; Green, Paul (2013): Estimating the Cost of Through-life Availability. In Tim Baines, B. Clegg, D. Harrison (Eds.): Proceedings of the Spring Servitization Conference (SSC2013).

Birmingham: Glasgow Caledonian University, pp. 175–181.

Purchase, Valerie; Parry, Glenn C.; Miller, John (2011): Service Enterprise Transformation. In Irene C. L. Ng, Glenn C. Parry, P. Wild, D. McFarlane, Paul Tasker (Eds.): Complex engineering service systems. Concepts and research. Berlin: Springer, pp. 25–48.

The Challenges of Costing Availability

Product failure has provided sustainable business for Original Equipment Manufacturers (OEMs) as profit has been made in fixing the problems encountered by the end user. However, this business model does not provide best value to the customer who encounters the failure or the provider who suffers reputational damage. Availability or performance-based contracts are seen as a viable alternative to the ‘product and support’ business model. Businesses now contracting for availability are paid to provide agreed levels of asset-related functionality such as Rolls Royce £865M contract with the UK Ministry of Defence and BAE Systems £446M Typhoon contract. These businesses recognise that the value of an asset is delivered ‘in use’, and seek competitive advantage by providing services that are critical to their customers’ core business processes.

Most models for costing availability, however, are framed having the ‘product and support’ business model in mind. The application of these models typically leads to hunting for broken components, and results in actions such as product redesign, or the purchase of additional spare parts.

Our view is that costing availability should support a service provider and its partners in their ability to respond timely and effectively to a demand for functional assets. We propose an approach to continuously evaluate and manage the cost of delivering to such a demand, by looking at the delivery system within which social and technical sub-systems dynamically interact to achieve a common purpose. At the heart of our approach is a defensible representation of the ‘whole’ delivery system as a set of purposeful activities together with the logical relationships between them.

Figure 1: Staged cost modelling.

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Identification & Representation of the System of Interest The identification and representation of the System of Interest (SOI) is based on the insight that availability is delivered through socio-technical systems. Therefore, data collected for example from interviews and documentation is appropriate in a context that is dominated by human activities. Other data sources may comprise free text fields from fault and repair reporting IT systems or FRACAS reports.

Identification of the SOI involves:

1. The relevant system elements; These can, for example be organisational units, activities, locations and functions.

2. The relationships between the elements and with the environment; Relationships between the relevant system elements can reflect the exchange of documentation and material, IT

systems, monetary transactions and personnel moving between locations.

3. The system boundaries;

The system boundaries can be blurred due to the overlap of processes and activities that contribute to the delivery of availability and to other outcomes. Hence, we distinguish between what is ‘inside’ and what is outside of the SOI depending on the ability to take action on the elements or links identified

Different perspectives on the delivery system significantly enhance the understanding that can be gained about how the delivery system functions. Perspectives can comprise organisation-centred viewpoints, functional views, and specific scenarios that blend functional and organisational viewpoints. Figure 2 shows a high-level functional view of aircraft availability loosely following the IDEF0 modelling standard. The IDEF0 standard describes the creation of maps that support the communication, understanding and consensus of enterprise systems. IDEF0 maps can represent functions and relationships across organizational boundaries, incorporate resource as well as data, information and knowledge flow. While being well-structured IDEF0 maps allow the user to designate the elements according to the specific context supporting the alignment of terminology and meaning across functions and groups. Additionally, IDEF0 maps allow for a representation of detail as required for the particular purpose, and the introduction greater detail once it unfolds. The hierarchical structure of an IDEF0 map allows for the gradual introduction of detail in IDEF0 according to the level of insight the researcher has gained. Such characteristic can facilitate focusing a discussion on the specific area of interest.

Figure 2: A high-level process model of aircraft availability.



The other modelling technique we identified as suitable for our case were diagrams following the Functional Resonance Analysis Method (FRAM) (Hollnagel 2012). The FRAM is an approach, to explain outcomes of socio-technical systems by interactions between multiple system elements, rather than direct cause and effect relations between two elements. It has been developed for accident investigation and risk analysis, and is equipped to deal with socio-technical systems to provide insights into why and how they normally succeed and occasionally fail. One of its foundations is the assumption that success and failure exist for the same reasons. For service provision this viewpoint is highly valuable as the insights provided include the enabling conditions as well as threats for the delivery to be successful. FRAM is suitable for identifying holistic phenomena of socio-technical systems.

The representation of an operational service delivery system can provide context for the concepts of price, expenditure and costs. Figure 3 shows a simplified delivery system comprising processes of two organisations (‘Organisation A’ and ‘Organisation B’), delivering an ‘outcome’ to a customer who is not shown here. Material (or service) flows are depicted in solid red arrows, for example inputs and outputs. Material or service flows are represented with a ‘price’ tag which exhibit a corresponding flow (‘revenue/funding’ or ‘expenditure’, shown as blue dashed arrows) in monetary units. These two flows together represent a transactional relationship between the material or service provider and the respective customer. An example is the relationship between ‘Organisation A’ and ‘Supplier X’. ‘Organisation A’ requires an input for one of the processes involved in the PSS, is charged a ‘price’, and has ‘expenditure’, i.e. an outflow of money to complete the transaction with the ‘Supplier X’.

Figure 3: Key concepts and their relationships .

6 Costing for Availability

Further readingsThenent, Nils Elias (2014): The Representation of an Advanced Service delivered by a Product Service System. A qualitative model of Avionics Availability. PhD. University of Bath, Bath, UK. Department of Mechanical Engineering. Available online at http://opus.bath.ac.uk/41233/.

Hollnagel, Erik (2012): FRAM, the functional resonance analysis method. Modelling complex socio-technical systems. Farnham, Surrey, UK England, Burlington, VT: Ashgate.

Draft Federal Information Processing Standards Publication 183, 12/21/1993: Integration definition for function modeling (IDEF0).

Within the SOI the exchange of material and services is not accompanied by a monetary transaction. Rather, the monetary value of transactions, ‘costs’, needs to be worked out. In the example in Figure 3, processes from ‘Organisation A’ provide multiple outputs, one of which is required by ‘Organisation B’ and as such contributes to the delivery of the desired outcome. At the same time ‘Organisation B’ provides material or services to enable ‘Organisation A’ to deliver its outputs. However, because no monetary transaction is involved with each delivery between the two organisations, the monetary value of these deliveries needs to be attributed to them. Only by costing the PSS internal transactions the ‘costs’ of delivering the ‘outcome’ can be determined. Multiple deliveries and organisation-internal splits where parts of the organisation are not involved in the PSS delivery complicate the attribution of monetary value to individual cost objects, be they activities or outputs.

If greater detail is required then further processes could be identified within Organisation A and Organisation B. The level of detail that is required depends on the specific purpose of the model and the areas actions can be taken on.

While we used the qualitative representation of the SOI to translate it into a quantitative cost model, as described in the following section, qualitative maps can also be utilised for:

− Business process analysis and business process redesign;− Support finding agreement on the SOI between different stakeholders;− Risk analysis, for example based on FRAM;− Identification of interruptions to information or material flow;− Evaluation of organisational structure.


Quantification

The conceptual model is the foundation for our quantitative modelling and costing of availability. The first step is to provide a mathematically treatable counterpart to the diagrammatic representation of the SOI. To ensure that a PSS is represented and treated mathematically as a ‘system’ in which multiple interrelated events happen concurrently we employ Petri Networks (PN):

− As a graphical tool, PN preserve the structure of a SOI specified in a diagrammatic representation, and allow the inclusion of the SOI’s states on such structure;

− As a mathematical tool, PN transform the diagrammatic representation of the SOI in its algebraic counterpart, so that its behaviour can be modelled quantitatively.

This modelling approach is particularly useful to determine both graphically and analytically whether some desired system state could be reached from a certain initial state. Analogously, one may investigate the repercussions of a certain sequence of events on the SOI’s state.

A simplified example of PN is shown in Figure 4. Events that may occur within the system are pictorially represented as bars; the pre and post-conditions for the occurrence of such events are represented as circles; the fulfilment of such pre and post-conditions, which ultimately defines the current state of the SOI, is denoted by the presence of dots (tokens) within certain circles.

Figure 4: A Petri-net model of for a sub-set of a hypothetical PSS delivering availability.

Circles Rectangles (system states) (actions)

p0 Committable and operable resource t0 Start calling upon resource (demand for usage to be met)

p1 Other pre-conditions being met t1 End calling upon resource (successful deployment)

p2 Resource being called upon t2 Detect failure occurrence

p3 Resource needing sustainment intervention t3 Carry out intervention upon failure (succesfully)


To integrate a model of the structure and behaviour of the SOI (e.g., in terms of materials and energy flows), and a model of the monetary worth attributed to the outputs realized and input utilized in reaching the desired states of the SOI we employ a unique combination of PN and Input-Output Analysis (IOA) to. From a mathematical viewpoint, both IOA and PN describe interdependencies within the SOI similarly. Therefore they can be combined to investigate whether the system is capable to sustain itself while delivering to some final demand, and obtain monetary evaluation of the system’s delivery.

Since time lags in delivery are typically part of availability-based contracting, we introduce the time dimension explicitly in our modelling approach. This allows us to investigate how desired states can be reached over time by synchronization of time-lagged demand and supply across the interrelated activities within the SOI. Priorities and capacity constraints become particularly crucial at this stage.

In the case of availability provision for repairable items, the SOI has to respond to recurrence of failure events over time to reach a state in which the item is usable again. To model the occurrence of ‘undesired’ events over time we have formulated a strategy for the statistical analysis of reliability data, and applied it to the real-life data provided by our industrial partners. Figure 5 illustrates some elements of the proposed strategy especially related to the preliminary exploration of the available data that may undermine event a mathematically sound analysis, if ignored.

The strategy has guided us in the selection of the most appropriate statistical modelling options and specific analytical formulations to describe recurrent events for fielded repairable technical systems. The results obtained helped us in formulating the exogenous demand placed upon a service delivery system due to things going wrong. Considering a demand for assets that can be called upon, and the occurrence of functional failures over time, our dynamic model simultaneously determines which activities within the SOI are triggered, to which level, and when, as well as how the SOI’s state evolves over time to reach a desired final state from its initial state (Figure 6).

Figure 5: Elements of a strategy for field data analysis.


Finally, the model of the SOI’s behaviour outlined so far provides the basis for modelling costs as an expression, in monetary terms, of the complex and interrelated consequences of changes occurring within the context in which a certain offering is delivered. In this light, a cost counterpart to the model outlined so far, attributes a monetary worth to the outputs realized and input utilized in reaching the desired states of the SOI over time. This is realised following the principle of Input Output Analysis (IOA) that the unknown cost of realizing each activity’s output is dependent upon the cost of all others, just like the levels at which an activity is required to operate potentially depend on all others time.

Figure 6: Results showing the activation of activities and stock levels required to meet the demand.

Further readingsSettanni, Ettore; Thenent, Nils Elias; Newnes, Linda B. (2013): System modeling: a foundation for costing through-life availability provision. In Alain Bernard, Louis Rivest, Debasish Dutta (Eds.): Product Lifecycle Management for Society. 10th IFIP WG 5.1 International Conference, PLM 2013, Nantes, France, July 8-10, 2013, Proceedings: Springer Berlin Heidelberg (IFIP Advances in Information and Communication Technology, 409), pp. 48–57.


Way forward

The ‘real world’ is complex, messy and contains people. The ambition of the approach briefly described in this booklet is not to describe the world; rather, to describe a way of thinking about the real world in a comprehensible, precise and defensible way. Figure 7 shows the path towards an integrated systems and cost model following our system-based approach.The above discussion initiated from the challenge of seeing availability as a service delivered through a socio-technical system, rather than as a property that, once designed into a product, holds indefinitely. Then, we have stressed that, in such a context, cost is an ‘emergent property’ of the service delivery system. To understand and model this system we employ a qualitative representation that underpins the quantitative model. Our final aim is to base the assessment of cost on a defensible understanding of the service delivery system to assist in taking appropriate actions.

Figure 7: The path towards an integrated system and cost model for availability.

Figure 8: Whole-system representation to prevent local optimisation (Source: Thenent 2014).

The way forward in costing advanced services – in particular availability – requires more emphasis on understanding how we know what we know in cost estimation. The uncritical application of familiar techniques based on “pockets” of knowledge” about the technical system element (the product) may well generate a number. However, not always being grounded on an understanding of what the delivery system is, those numbers are often unable to support a cost conscious management of such a system over time and may foster local optimisation, as shown in Figure 8. The systems-based approach we suggest that combines quantitative modelling and optimisation with qualitative mapping leads the way into cost conscious decision-making in availability provision.

Further readingsThenent, Nils Elias; Settanni, Ettore; Parry, Glenn; Goh, Yee Mey; Newnes, Linda B. (2014): Cutting cost in service systems. Are you running with scissors? In Strategic Change: Special Issue: Servitization 23 (5-6), pp. 341–357. Available online at 10.1002/jsc.1981.

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